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Milk mid-infrared (MIR) spectra, already recorded in routine, offer a potential alternative, as heat stress affects milk composition and is therefore expected to be reflected in MIR spectra. This study thus aimed to develop a MIR prediction equation for individual heat stress response. Surface temperature and milk traits from 399 cows were recorded to develop a combined heat stress response phenotype. This phenotype resulted from two equations: one predicting surface body temperature (R\n                    <jats:sup>2<\/jats:sup>\n                    \u2009=\u20090.67; RMSE\u2009=\u20090.64\u00a0\u00b0C) and one classifying records into three heat stress response classes based on surface temperature and milk composition (accuracy\u2009=\u200961%). The final prediction was applied to historical milk recording data associated with weather information to assess external validity. A mixed model was also fitted to identify cow characteristics associated with stronger predicted heat stress responses. As reported in the literature, multiparous cows, in early lactation, with the highest 24\u00a0h milk yield tended to be more affected. Overall, the prediction developed in this study shows strong potential for routine heat stress detection.\n                  <\/jats:p>","DOI":"10.1038\/s41598-026-39287-9","type":"journal-article","created":{"date-parts":[[2026,3,19]],"date-time":"2026-03-19T18:14:14Z","timestamp":1773944054000},"update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":2,"title":["Prediction of heat stress response in dairy cows using milk mid-infrared spectra"],"prefix":"10.1038","volume":"16","author":[{"given":"Pauline","family":"Lemal","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Cl\u00e9ment","family":"Grelet","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Fr\u00e9d\u00e9ric","family":"Dehareng","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"H\u00e9l\u00e8ne","family":"Soyeurt","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Martine","family":"Schroyen","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Nicolas","family":"Gengler","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"297","published-online":{"date-parts":[[2026,3,19]]},"reference":[{"key":"39287_CR1","doi-asserted-by":"publisher","first-page":"8645","DOI":"10.3168\/jds.2017-12651","volume":"100","author":"L Polsky","year":"2017","unstructured":"Polsky, L. & von Keyserlingk, M. 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